SoftGrasp: Adaptive grasping for dexterous hand based on multimodal imitation learning
Biomimetic grasping is crucial for robots to interact with the environment and perform complex tasks, making it a key focus in robotics and embodied intelligence. However, achieving human-level finger coordination and force control remains challenging due to the need for multimodal perception, inclu...
Saved in:
| Main Authors: | Yihong Li, Ce Guo, Junkai Ren, Bailiang Chen, Chuang Cheng, Hui Zhang, Huimin Lu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
|
| Series: | Biomimetic Intelligence and Robotics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667379725000087 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Design and Experimental Evaluation of a Sensorimotor-Inspired Grasping Strategy for Dexterous Prosthetic Hands
by: Ting Zhang, et al.
Published: (2023-01-01) -
Biomechanical Analysis of the Effect of Finger Joint Configuration on Hand Grasping Performance: Rigid vs Flexible
by: Yuyang Wei, et al.
Published: (2023-01-01) -
Recent Improvements in the Development of Soft Grippers Capable of Dexterous Manipulation
by: Manuela Otti, et al.
Published: (2024-12-01) -
A Fast Grasp Planning Algorithm for Humanoid Robot Hands
by: Ziqi Liu, et al.
Published: (2024-10-01) -
Multimodal Deep Learning Model for Cylindrical Grasp Prediction Using Surface Electromyography and Contextual Data During Reaching
by: Raquel Lázaro, et al.
Published: (2025-02-01)